Todays artificial intelligence is certainly formidable. It can beat world champions at intricate games like chess and Go, or dominate at Jeopardy!. It can interpret heaps of data for us, guide driverless cars, respond to spoken commands, and track down the answers to your internet search queries.
And as artificial intelligence becomes more sophisticated, there will be fewer and fewer jobs that robots cant take care ofor so Elon Musk recently speculated. He suggested that we might have to give our own brains a boost to stay competitive in an AI-saturated job market.
But if AI does steal your job, it wont be because scientists have built a brain better than yours. At least, not across the board. Most of the advances in artificial intelligence have been focused on solving particular kinds of problems. This narrow artificial intelligence is great at specific tasks like recommending songs on Pandora or analyzing how safe your driving habits are. However, the kind of general artificial intelligence that would simulate a person is a long ways off.
At the very beginning of AI there was a lot of discussion about more general approaches to AI, with aspirations to create systemsthat would work on many different problems, says John Laird, a computer scientist at the University of Michigan. Over the last 50 years the evolution has been towards specialization.
Still, researchers are honing AIs skills in complex tasks like understanding language and adapting to changing conditions. The really exciting thing is that computer algorithms are getting smarter in more general ways, says David Hanson, founder and CEO of Hanson Robotics in Hong Kong, who builds incredibly lifelike robots.
And there have always been people interested in how these aspects of AI might fit together. They want to know: How do you create systems that have the capabilities that we normally associate with humans? Laird says.
So why dont we have general AI yet?
There isn't a single, agreed-upon definition for general artificial intelligence. Philosophers will argue whether General AI needs to have a real consciousness or whether a simulation of it suffices," Jonathan Matus, founder and CEO of Zendrive, which is based in San Francisco and analyzes driving data collected from smartphone sensors, said in an email.
But, in essence, General intelligence is what people do, says Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence in Seattle, Washington. We dont have a computer that can function with the capabilities of a six year old, or even a three year old, and so were very far from general intelligence.
Such an AI would be able to accumulate knowledge and use it to solve different kinds of problems. I think the most powerful concept of general intelligence is that its adaptive, Hanson says. If you learn, for example, how to tie your shoes, you could apply it to other sorts of knots in other applications. If you have an intelligence that knows how to have a conversation with you, it can also know what it means to go to the store and buy a carton of milk.
General AI would need to have background knowledge about the world as well as common sense, Laird says. Pose it a new problem, its able to sort of work its way through it, and it also has a memory of what its been exposed to.
Scientists have designed AI that can answer an array of questions with projects like IBMs Watson, which defeated two former Jeopardy! champions in 2011. It had to have a lot of general capabilities in order to do that, Laird says.
Today, there are many different Watsons, each tweaked to perform services such as diagnosing medical problems, helping businesspeople run meetings, and making trailers for movies about super-smart AI. Still, Its not fully adaptive in the humanlike way, so it really doesnt match human capabilities, Hanson says.
Were still figuring out the recipe for general intelligence. One of the problems we have is actually defining what all these capabilities are and then asking, how can you integrate them together seamlessly to produce coherent behavior? Laird says.
And for now, AI is facing something of a paradox. Things that are so hard for people, like playing championship-level Go and poker have turned out to be relatively easy for the machines, Etzioni says. Yet at the same time, the things that are easiest for a personlike making sense of what they see in front of them, speaking in their mother tonguethe machines really struggle with.
The strategies that help prepare an AI system to play chess or Go are less helpful in the real world, which does not operate within the strict rules of a game. Youve got Deep Blue that can play chess really well, youve got AlphaGo that can play Go, but you cant walk up to either of them and say, ok were going to play tic-tac-toe, Laird says. There are these kinds of learning that are not youre not able to do just with narrow AI.
What about things like Siri and Alexa?
A huge challenge is designing AI that can figure out what we mean when we speak. Understanding of natural language is what sometimes is called AI complete, meaning if you can really do that, you can probably solve artificial intelligence, Etzioni says.
Were making progress with virtual assistants such as Siri and Alexa. Theres a long way to go on those systems, but theyre starting to have to deal with more of that generality, Laird says. Still, he says, once you ask a question, and then you ask it another question, and another question, its not like youre developing a shared understanding of what youre talking about.
In other words, they can't hold up their end of a conversation. They dont really understand what you say, the meaning of it, Etzioni says. Theres no dialogue, theres really no background knowledge and as a resultthe systems misunderstanding of what we say is often downright comical.
Extracting the full meaning of informal sentences is tremendously difficult for AI. Every word matters, as does word order and the context in which the sentence is spoken. There are a lot of challenges in how to go from language to an internal representation of the problem that the system can then use to solve a problem, Laird says.
To help AI handle natural language better, Etzioni and his colleagues are putting them through their paces with standardized tests like the SAT. I really think of it as an IQ test for the machine, Etzioni says. And guess what? The machine doesnt do very well.
In his view, exam questions are a more revealing measure of machine intelligence than the Turing Test, which chatbots often pass by resorting to trickery.
To engage in a sophisticated dialogue, to do complex question and answering, its not enough to just work with the rudiments of language, Etzioni says. It ties into your background knowledge, it ties into your ability to draw conclusions.
Lets say youre taking a test and find yourself faced with the question: what happens if you move a plant into a dark room? Youll need an understanding of language to decipher the question, scientific knowledge to inform you what photosynthesis is, and a bit of common sensethe ability to realize that if light is necessary for photosynthesis, a plant wont thrive when placed in a shady area.
Its not enough to know what photosynthesis is very formally, you have to be able to apply that knowledge to the real world, Etzioni says.
Will general AI think like us?
Researchers have gained a lot of ground with AI by using what we know about how the human brain. Learning a lot about how humans work from psychology and neuroscience is a good way to help direct the research, Laird says.
One promising approach to AI, called deep learning, is inspired by the architecture of neurons in the human brain. Its deep neural networks gather human amounts of data and sniff out patterns. This allows it to make predictions or distinctions, like whether someone uttered a P or a B, or if a picture features a cat or a dog.
These are all things that the machines are exceptionally good at, and [they] probably have developed superhuman patter recognition abilities, Etzioni says. But thats only a small part of what is general intelligence.
Ultimately, how humans think is grounded in the feelings within our bodies, and influenced by things like our hormones and physical sensations. Its going to be a long time before we can create an effective simulation of all of that, Hanson says.
We might one day build AI that is inspired by how humans think, but does not work the same way. After all, we didnt need to make airplanes flap their wings. Instead we built airplanes that fly, but they do that using very different technology, Etzioni says.
Still, we might want to keep some especially humanoid featureslike emotion. People run the world, so having AI that understand and gets along with people can be very, very useful, says Hanson, who is trying to design empathetic robots that care about people. He considers emotion to be an integral part of what goes into general intelligence.
Plus, the more humanoid a general AI is designed to be, the easier it will be to tell how well it works. If we create an alien intelligence thats really unlike humans, we dont know exactly what hallmarks for general intelligence to look for, Hanson says. Theres a bigger concern for me which is that, if its alien are we going to trust it? Is it going to trust us? Are we going to have a good relationship with it?
When will it get here?
So, how will we use general AI? We already have targeted AI to solve specific problems. But general AI could help us solve them better and faster, and tackle problems that are complex and call for many types of skills. The systems that we have today are far less sophisticated than we could imagine, Etzioni says. If we truly had general AI we would be saving lives left and right.
The Allen Institute has designed a search engine for scientists called Semantic Scholar. The kind of search we do, even with the targeted AI we put in, is nowhere near what scientists need, Etzioni says. Imagine a scientist helperthat helps our scientists solve humanitys thorniest problems, whether its climate change or cancer or superbugs.
Or it could give strategic advice to governments, Matus says. It could also be used to plan and execute super complex projects, like a mission to Mars, a political campaign, or a hostile takeover of a public company."
People could also benefit from general AI in their everyday lives. It could assist elderly or disabled people, improve customer service, or tutor us. When it comes to a learning assistant, it could understand your learning weaknesses and find your strengths to help you step up and plan a program for improving your capabilities, Hanson says. I see it helping people realize their dreams.
But all this is a long way off. Were so far away fromeven six-year-old level of intelligence, let alone full general human intelligence, let alone super-intelligence, Etzioni says. He surveyed other leaders in the field of AI, and found that most of them believed super-intelligent AI was 25 years or more away. Most scientists agree that human-level intelligence is beyond the foreseeable horizon, he says.
General artificial intelligence does raise a few concerns, although machines run amok probably wont be one of them. Im not so worried about super-intelligence and Terminator scenarios, frankly I think those are quite farfetched, Etzioni says. But Im definitely worried about the impact on jobs and unemployment, and this is already happening with the targeted systems.
And like any tool, general artificial intelligence could be misused. Such technologies have the potential for tremendous destabilizing effects in the hands of any government, research organization or company, Matus says. This simply means that we need to be clever in designing policy and systems that will keep stability and give humans alternative sources of income and occupation. People are pondering solutions like universal basic income to cope with narrow AI's potential to displace workers.
Ultimately, researchers want to beef up artificial intelligence with more general skills so it can better serve humans. Were not going to see general AI initially to be anything like I, Robot. Its going to be things like Siri and stuff like that, which will augment and help people, Laird says. My hope is that its really going be something that makes you a better person, as opposed to competes with you.
Read the rest here:
There are two kinds of AI, and the difference is important - Popular Science
- Classic reasoning systems like Loom and PowerLoom vs. more modern systems based on probalistic networks - November 8th, 2009 [November 8th, 2009]
- Using Amazon's cloud service for computationally expensive calculations - November 8th, 2009 [November 8th, 2009]
- Software environments for working on AI projects - November 8th, 2009 [November 8th, 2009]
- New version of my NLP toolkit - November 8th, 2009 [November 8th, 2009]
- Semantic Web: through the back door with HTML and CSS - November 8th, 2009 [November 8th, 2009]
- Java FastTag part of speech tagger is now released under the LGPL - November 8th, 2009 [November 8th, 2009]
- Defining AI and Knowledge Engineering - November 8th, 2009 [November 8th, 2009]
- Great Overview of Knowledge Representation - November 8th, 2009 [November 8th, 2009]
- Something like Google page rank for semantic web URIs - November 8th, 2009 [November 8th, 2009]
- My experiences writing AI software for vehicle control in games and virtual reality systems - November 8th, 2009 [November 8th, 2009]
- The URL for this blog has changed - November 8th, 2009 [November 8th, 2009]
- I have a new page on Knowledge Management - November 8th, 2009 [November 8th, 2009]
- N-GRAM analysis using Ruby - November 8th, 2009 [November 8th, 2009]
- Good video: Knowledge Representation and the Semantic Web - November 8th, 2009 [November 8th, 2009]
- Using the PowerLoom reasoning system with JRuby - November 8th, 2009 [November 8th, 2009]
- Machines Like Us - November 8th, 2009 [November 8th, 2009]
- RapidMiner machine learning, data mining, and visualization tool - November 8th, 2009 [November 8th, 2009]
- texai.org - November 8th, 2009 [November 8th, 2009]
- NLTK: The Natural Language Toolkit - November 8th, 2009 [November 8th, 2009]
- My OpenCalais Ruby client library - November 8th, 2009 [November 8th, 2009]
- Ruby API for accessing Freebase/Metaweb structured data - November 8th, 2009 [November 8th, 2009]
- Protégé OWL Ontology Editor - November 8th, 2009 [November 8th, 2009]
- New version of Numenta software is available - November 8th, 2009 [November 8th, 2009]
- Very nice: Elsevier IJCAI AI Journal articles now available for free as PDFs - November 8th, 2009 [November 8th, 2009]
- Verison 2.0 of OpenCyc is available - November 8th, 2009 [November 8th, 2009]
- What’s Your Biggest Question about Artificial Intelligence? [Article] - November 8th, 2009 [November 8th, 2009]
- Minimax Search [Knowledge] - November 8th, 2009 [November 8th, 2009]
- Decision Tree [Knowledge] - November 8th, 2009 [November 8th, 2009]
- More AI Content & Format Preference Poll [Article] - November 8th, 2009 [November 8th, 2009]
- New Planners Solve Rescue Missions [News] - November 8th, 2009 [November 8th, 2009]
- Neural Network Learns to Bluff at Poker [News] - November 8th, 2009 [November 8th, 2009]
- Pushing the Limits of Game AI Technology [News] - November 8th, 2009 [November 8th, 2009]
- Mining Data for the Netflix Prize [News] - November 8th, 2009 [November 8th, 2009]
- Interview with Peter Denning on the Principles of Computing [News] - November 8th, 2009 [November 8th, 2009]
- Decision Making for Medical Support [News] - November 8th, 2009 [November 8th, 2009]
- Neural Network Creates Music CD [News] - November 8th, 2009 [November 8th, 2009]
- jKilavuz - a guide in the polygon soup [News] - November 8th, 2009 [November 8th, 2009]
- Artificial General Intelligence: Now Is the Time [News] - November 8th, 2009 [November 8th, 2009]
- Apply AI 2007 Roundtable Report [News] - November 8th, 2009 [November 8th, 2009]
- What Would You do With 80 Cores? [News] - November 8th, 2009 [November 8th, 2009]
- Software Finds Learning Language Child's Play [News] - November 8th, 2009 [November 8th, 2009]
- Artificial Intelligence in Games [Article] - November 8th, 2009 [November 8th, 2009]
- Artificial Intelligence Resources - November 8th, 2009 [November 8th, 2009]
- Alan Turing: Mathematical Biologist? - April 25th, 2012 [April 25th, 2012]
- BBC Horizon: The Hunt for AI ( Artificial Intelligence ) - Video - April 30th, 2012 [April 30th, 2012]
- Can computers have true artificial intelligence" Masonic handshake" 3rd-April-2012 - Video - April 30th, 2012 [April 30th, 2012]
- Kevin B. Korb - Interview - Artificial Intelligence and the Singularity p3 - Video - April 30th, 2012 [April 30th, 2012]
- Artificial Intelligence - 6 Month Anniversary - Video - April 30th, 2012 [April 30th, 2012]
- Science Breakthroughs - April 30th, 2012 [April 30th, 2012]
- Hitman: Blood Money - Part 49 - Stupid Artificial Intelligence! - Video - April 30th, 2012 [April 30th, 2012]
- Research Members Turned Off By HAARP Artificial Intelligence - Video - April 30th, 2012 [April 30th, 2012]
- Artificial Intelligence Lecture No. 5 - Video - April 30th, 2012 [April 30th, 2012]
- The Artificial Intelligence Laboratory, 2012 - Video - April 30th, 2012 [April 30th, 2012]
- Charlie Rose - Artificial Intelligence - Video - April 30th, 2012 [April 30th, 2012]
- Expert on artificial intelligence to speak at EPIIC Nights dinner - May 4th, 2012 [May 4th, 2012]
- Filipino software engineers complete and best thousands on Stanford’s Artificial Intelligence Course - May 4th, 2012 [May 4th, 2012]
- Vodafone xone™ Hackathon Challenges Developers and Entrepreneurs to Build a New Generation of Artificial Intelligence ... - May 4th, 2012 [May 4th, 2012]
- Rocket Fuel Packages Up CPG Booster - May 4th, 2012 [May 4th, 2012]
- 2 Filipinos finishes among top in Stanford’s Artificial Intelligence course - May 5th, 2012 [May 5th, 2012]
- Why Your Brain Isn't A Computer - May 5th, 2012 [May 5th, 2012]
- 2 Pinoy software engineers complete Stanford's AI course - May 7th, 2012 [May 7th, 2012]
- Percipio Media, LLC Proudly Accepts Partnership With MIT's Prestigious Computer Science And Artificial Intelligence ... - May 10th, 2012 [May 10th, 2012]
- Google Driverless Car Ok'd by Nevada - May 10th, 2012 [May 10th, 2012]
- Moving Beyond the Marketing Funnel: Rocket Fuel and Forrester Research Announce Free Webinar - May 10th, 2012 [May 10th, 2012]
- Rocket Fuel Wins 2012 San Francisco Business Times Tech & Innovation Award - May 13th, 2012 [May 13th, 2012]
- Internet Week 2012: Rocket Fuel to Speak at OMMA RTB - May 16th, 2012 [May 16th, 2012]
- How to Get the Most Out of Your Facebook Ads -- Rocket Fuel's VP of Products, Eshwar Belani, to Lead MarketingProfs ... - May 16th, 2012 [May 16th, 2012]
- The Digital Disruptor To Banking Has Just Gone International - May 16th, 2012 [May 16th, 2012]
- Moving Beyond the Marketing Funnel: Rocket Fuel Announce Free Webinar Featuring an Independent Research Firm - May 23rd, 2012 [May 23rd, 2012]
- MASA Showcases Latest Version of MASA SWORD for Homeland Security Markets - May 23rd, 2012 [May 23rd, 2012]
- Bluesky Launches Drones for Aerial Surveying - May 23rd, 2012 [May 23rd, 2012]
- Artificial Intelligence: What happened to the hunt for thinking machines? - May 25th, 2012 [May 25th, 2012]
- Bubble Robots Move Using Lasers [VIDEO] - May 25th, 2012 [May 25th, 2012]
- UHV assistant professors receive $10,000 summer research grants - May 27th, 2012 [May 27th, 2012]
- Artificial intelligence: science fiction or simply science? - May 28th, 2012 [May 28th, 2012]
- Exetel taps artificial intelligence - May 29th, 2012 [May 29th, 2012]
- Software offers brain on the rain - May 29th, 2012 [May 29th, 2012]
- New Dean of Science has high hopes for his faculty - May 30th, 2012 [May 30th, 2012]
- Cognitive Code Announces "Silvia For Android" App - May 31st, 2012 [May 31st, 2012]
- A Rat is Smarter Than Google - June 5th, 2012 [June 5th, 2012]